Diagnostic indicators for integrated assessment models of climate policy

Abstract

International audienceIntegrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results

Comparison and interactions between the long-term pursuit of energy independence and climate policies

“…(1) See Methods for discussion of which fuels are depicted in which model. (2) The TI-p or the Transformation Index (primary energy) classification of model behavior under carbon taxes from Kriegler et al 9 . "Low" indicates a relatively smaller transformation of primary energy supply compared to other models whereas "High" indicates a relatively larger transformation of the primary energy system compared to other models.…”

“…"Low" indicates a relatively smaller transformation of primary energy supply compared to other models whereas "High" indicates a relatively larger transformation of the primary energy system compared to other models. (3) CoEI or the carbon intensity over energy intensity indicator characterizes model behavior under carbon taxes from Kriegler et al 9 . "Low" indicates models which have a stronger reduction in carbon intensity relative to energy intensity compared to other models whereas "High" indicates models which have a stronger demand response compared to growth in low carbon energy sources.…”

“…The models differ in their representation of the economy (equilibrium type), modeling approach and representation of energy trade. In addition, this table includes two diagnostic indicators which have been recently developed for IAMs to capture two aspects of a model's response to a given carbon price 9 . The first is its relative response in transforming primary energy supply (TI-p) compared to other models.…”

Energy technology roll-out for climate change mitigation: A multi-model study for Latin America

“…We particularly zoom in on electricity generation, as in developing countries (and especially in Latin America), this sector is likely to grow fast over the decades to come, with a two-to three-fold expansion between today and 2050 (see for example IEA-ETP, 2012. A number of recent studies have shown that the decarbonization of non-electric energy supply, such as in the transport sector and industry, poses crucial challenges for low atmospheric CO 2 concentration stabilization, since either fewer technology options exist or low-carbon technologies abound but are more expensive than for electricity generation (see e.g., Krey et al, 2014;Kriegler et al, 2014aKriegler et al, , 2014bLuderer et al, 2012;Rösler et al, 2014;van der Zwaan et al, 2013a). A detailed inspection of these other sectors, however, is beyond the scope of the present paper.…”

“…In this paper we also inspect the reasons for differences in technology roll-out that we observe across models, some of which relate to structural differences between models, others to different parameter assumptions (see e.g. Kriegler et al, 2014aKriegler et al, , 2014b, who present results of extensive analysis in an effort to do the same through novel work on the basis of diagnostic indicators).…”